Volumetric 3D stitching of optical coherence tomography volumes
Optical coherence tomography (OCT) is a noninvasive medical imaging modality, which provides highresolution transectional images of biological tissue. However, its potential is limited due to a relatively small field of view. To overcome this drawback, we describe a scheme for fully automated stitch...
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Online Access: | https://doi.org/10.1515/cdbme-2018-0079 |
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doaj-791af2fb10fb49cd82622dde3a05bf482021-09-06T19:19:26ZengDe GruyterCurrent Directions in Biomedical Engineering2364-55042018-09-014132733010.1515/cdbme-2018-0079cdbme-2018-0079Volumetric 3D stitching of optical coherence tomography volumesLaves Max-Heinrich0Kahrs Lüder A.1Ortmaier Tobias2Institute of Mechatronic Systems, Appelstr. 11A, 30167Hannover, GermanyInstitute of Mechatronic Systems, Appelstr. 11A, 30167Hannover, GermanyInstitute of Mechatronic Systems, Appelstr. 11A, 30167Hannover, GermanyOptical coherence tomography (OCT) is a noninvasive medical imaging modality, which provides highresolution transectional images of biological tissue. However, its potential is limited due to a relatively small field of view. To overcome this drawback, we describe a scheme for fully automated stitching of multiple 3D OCT volumes for panoramic imaging. The voxel displacements between two adjacent images are calculated by extending the Lucas-Kanade optical flow a lgorithm to dense volumetric images. A RANSAC robust estimator is used to obtain rigid transformations out of the resulting flow v ectors. T he i mages a re t ransformed into the same coordinate frame and overlapping areas are blended. The accuracy of the proposed stitching scheme is evaluated on two datasets of 7 and 4 OCT volumes, respectively. By placing the specimens on a high-accuracy motorized translational stage, ground truth transformations are available. This results in a mean translational error between two adjacent volumes of 16.6 ± 0.8 μm (2.8 ± 0.13 voxels). To the author’s knowledge, this is the first reported stitching of multiple 3D OCT volumes by using dense voxel information in the registration process. The achieved results are sufficient for providing high accuracy OCT panoramic images. Combined with a recently available high-speed 4D OCT, our method enables interactive stitching of hand-guided acquisitions.https://doi.org/10.1515/cdbme-2018-0079medical imagingimage processingregistrationpanoramic imagingmosaicingoptical flow |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Laves Max-Heinrich Kahrs Lüder A. Ortmaier Tobias |
spellingShingle |
Laves Max-Heinrich Kahrs Lüder A. Ortmaier Tobias Volumetric 3D stitching of optical coherence tomography volumes Current Directions in Biomedical Engineering medical imaging image processing registration panoramic imaging mosaicing optical flow |
author_facet |
Laves Max-Heinrich Kahrs Lüder A. Ortmaier Tobias |
author_sort |
Laves Max-Heinrich |
title |
Volumetric 3D stitching of optical coherence tomography volumes |
title_short |
Volumetric 3D stitching of optical coherence tomography volumes |
title_full |
Volumetric 3D stitching of optical coherence tomography volumes |
title_fullStr |
Volumetric 3D stitching of optical coherence tomography volumes |
title_full_unstemmed |
Volumetric 3D stitching of optical coherence tomography volumes |
title_sort |
volumetric 3d stitching of optical coherence tomography volumes |
publisher |
De Gruyter |
series |
Current Directions in Biomedical Engineering |
issn |
2364-5504 |
publishDate |
2018-09-01 |
description |
Optical coherence tomography (OCT) is a noninvasive medical imaging modality, which provides highresolution transectional images of biological tissue. However, its potential is limited due to a relatively small field of view. To overcome this drawback, we describe a scheme for fully automated stitching of multiple 3D OCT volumes for panoramic imaging. The voxel displacements between two adjacent images are calculated by extending the Lucas-Kanade optical flow a lgorithm to dense volumetric images. A RANSAC robust estimator is used to obtain rigid transformations out of the resulting flow v ectors. T he i mages a re t ransformed into the same coordinate frame and overlapping areas are blended. The accuracy of the proposed stitching scheme is evaluated on two datasets of 7 and 4 OCT volumes, respectively. By placing the specimens on a high-accuracy motorized translational stage, ground truth transformations are available. This results in a mean translational error between two adjacent volumes of 16.6 ± 0.8 μm (2.8 ± 0.13 voxels). To the author’s knowledge, this is the first reported stitching of multiple 3D OCT volumes by using dense voxel information in the registration process. The achieved results are sufficient for providing high accuracy OCT panoramic images. Combined with a recently available high-speed 4D OCT, our method enables interactive stitching of hand-guided acquisitions. |
topic |
medical imaging image processing registration panoramic imaging mosaicing optical flow |
url |
https://doi.org/10.1515/cdbme-2018-0079 |
work_keys_str_mv |
AT lavesmaxheinrich volumetric3dstitchingofopticalcoherencetomographyvolumes AT kahrsludera volumetric3dstitchingofopticalcoherencetomographyvolumes AT ortmaiertobias volumetric3dstitchingofopticalcoherencetomographyvolumes |
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